Data Management Plan: Difference Between Macro and Macro Scales

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Never in the history of running a business or enterprise have it become an over-complex endeavor than today. It used to follow a simple data management plan that is applicable to all kinds of organizational set-ups.

It is as expected because of the rise of high-end technology that makes data management a hyper-connected digital highway nowadays. Terms like macro and micro scales preoccupy the minds of think tanks to define the degree of operation. Combining fluidity in strategy making and analytics in problem solving. Just what is the difference between using micro or macro data management still is dependent on age-old management principles.

As an important corporate asset, data must be collected, organized, stored and should serve to support objectives. As such data must be accurate and encompassing to be of value to the organization.

Data collection and storage systems requirements must be laid out and needs to be effectively charted and clearly understood.

Effective management can only be expected if datum comes from accurate information, particularly from areas that affect the organization.

Common data management standards, proven practices and guidelines must be followed. Includes among others defining, modeling, designing and documents data to improve quality, particularly when said data will be shared among systems and staff.

Whether it is macro or micro, both derives data from analytical approaches. However macro analytics is more qualitative in nature, while micro is quantitative.

Macro data management plan models is normally the starting point when comprehensive information is not yet available. Ignorance about the details drive planners to be more quantitative. Note that as one approaches ‘micro’ more data comes in to set the boundaries and the model will come out less generalized. In plain language a macro management plan defines the parameter by knowing what to do.

Micro analytic models are more scientific and specific perspective are drawn out of the system. It uses both boring methods of analysis and synthesis in developing the setup structure ensuing framework. It draws in detail what the available voluminous data suggests to the generation of metrics, progression and even logic validation. Micro data management in short is a plan of action as one is instructed on how to go about accomplishing the task.

The method of making a comprehensive data management plan must be a concerted combination of both macro and micro scale analytic. There is no clear distinction between the two, as one delves into the other as the organization progresses.